if (!require("dplyr")) install.packages("dplyr")
## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
if (!require("skimr")) install.packages("skimr")
## Loading required package: skimr
if (!require("tidyr")) install.packages("tidyr")
## Loading required package: tidyr
if (!require("survival")) install.packages("survival")
## Loading required package: survival
if (!require("survminer")) install.packages("survminer")
## Loading required package: survminer
## Loading required package: ggplot2
## Loading required package: ggpubr
##
## Attaching package: 'survminer'
## The following object is masked from 'package:survival':
##
## myeloma
if (!require("haven")) install.packages("haven")
## Loading required package: haven
if (!require("broom")) install.packages("broom")
## Loading required package: broom
if (!require("rms")) install.packages("rms")
## Loading required package: rms
## Loading required package: Hmisc
##
## Attaching package: 'Hmisc'
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##
## src, summarize
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##
## format.pval, units
if (!require("tidyverse")) install.packages("tidyverse")
## Loading required package: tidyverse
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats 1.0.0 ✔ readr 2.1.5
## ✔ lubridate 1.9.4 ✔ stringr 1.5.1
## ✔ purrr 1.0.4 ✔ tibble 3.2.1
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if (!require("tableone")) install.packages("tableone")
## Loading required package: tableone
library(dplyr)
library(skimr)
library(tidyr)
library(survival)
library(survminer)
library(haven)
library(broom)
library(rms)
library(tidyverse)
library(tableone)
NHANES2 <- read.csv("NHANES2-1 (1).csv")
d <- NHANES2 #%>%
#select('ROWNAMES','SEX','RACE','MARRY','DEATH','AGEYRS',
#'GRADES','WT', 'BOOZE', 'SIZE',
#'AVGSMK', "HEIGHT", "EXAM_YR", "DIE_YR", "LAST_YR")
#Exclude missing death
d <- d %>%
filter(!is.na(BOOZE), !is.na(DEATH), !is.na(SEX), !is.na(RACE), !is.na(GRADES), !is.na(MARRY), !is.na(AVGSMK), !is.na(SIZE), !is.na(GRADES))
#BMI
d <- d %>%
mutate(BMI = WT / (HEIGHT / 100)^2)
head(d$BMI)
## [1] 20.49522 21.02151 23.22748 35.72785 27.92312 30.50132
# GRADES and SIZE categories
d$EDUC_CAT <- cut(d$GRADES,
breaks = c(-Inf, 8, 11, 12, 15, Inf),
labels = c("≤8 yrs", "Some HS", "HS Grad", "Some College", "College+"),
right = TRUE)
d$SIZE_CAT <- cut(d$SIZE,
breaks = c(0, 3, 5, 7, 8),
labels = c("Rural", "Small town", "Medium city", "Large city"),
right = TRUE)
# Catergorical BOOZE
d <- d %>%
mutate(BOOZE_q = cut(
BOOZE,
breaks = c(-1, 0, 0.5, 2.0, 77.0),
include.lowest = TRUE,
labels = c("0/week", "0–0.5/week", "0.5–2/week", ">2/week")
))
vars <- c("AGEYRS", "SEX", "RACE", "MARRY", "BMI", "AVGSMK", "EDUC_CAT", "SIZE_CAT")
catVars <- c("SEX", "RACE", "MARRY")
#Table 1
table1 <- CreateTableOne(vars = vars,
data = d,
strata = "BOOZE_q",
factorVars = catVars)
print(table1, showAllLevels = TRUE)
## Stratified by BOOZE_q
## level 0/week 0–0.5/week 0.5–2/week
## n 4053 941 1729
## AGEYRS (mean (SD)) 57.09 (12.79) 54.34 (13.36) 51.60 (13.53)
## SEX (%) 1 1448 (35.7) 367 (39.0) 856 (49.5)
## 2 2605 (64.3) 574 (61.0) 873 (50.5)
## RACE (%) 1 3497 (86.3) 827 (87.9) 1515 (87.6)
## 2 475 (11.7) 93 ( 9.9) 194 (11.2)
## 3 81 ( 2.0) 21 ( 2.2) 20 ( 1.2)
## MARRY (%) 2 2885 (71.2) 683 (72.6) 1288 (74.5)
## 3 671 (16.6) 127 (13.5) 172 ( 9.9)
## 4 190 ( 4.7) 67 ( 7.1) 102 ( 5.9)
## 5 96 ( 2.4) 20 ( 2.1) 59 ( 3.4)
## 6 202 ( 5.0) 40 ( 4.3) 103 ( 6.0)
## 8 9 ( 0.2) 4 ( 0.4) 5 ( 0.3)
## BMI (mean (SD)) 26.55 (5.50) 26.42 (5.10) 26.03 (4.84)
## AVGSMK (mean (SD)) 4.82 (10.84) 6.72 (12.63) 8.26 (13.77)
## EDUC_CAT (%) ≤8 yrs 1452 (35.8) 217 (23.1) 337 (19.5)
## Some HS 753 (18.6) 185 (19.7) 282 (16.3)
## HS Grad 1209 (29.8) 311 (33.0) 636 (36.8)
## Some College 353 ( 8.7) 130 (13.8) 235 (13.6)
## College+ 286 ( 7.1) 98 (10.4) 239 (13.8)
## SIZE_CAT (%) Rural 1101 (27.2) 348 (37.0) 758 (43.8)
## Small town 454 (11.2) 123 (13.1) 244 (14.1)
## Medium city 569 (14.0) 118 (12.5) 205 (11.9)
## Large city 1929 (47.6) 352 (37.4) 522 (30.2)
## Stratified by BOOZE_q
## >2/week p test
## n 2527
## AGEYRS (mean (SD)) 51.71 (13.18) <0.001
## SEX (%) 1678 (66.4) <0.001
## 849 (33.6)
## RACE (%) 2250 (89.0) 0.010
## 236 ( 9.3)
## 41 ( 1.6)
## MARRY (%) 1972 (78.0) <0.001
## 170 ( 6.7)
## 168 ( 6.6)
## 70 ( 2.8)
## 140 ( 5.5)
## 7 ( 0.3)
## BMI (mean (SD)) 25.20 (4.08) <0.001
## AVGSMK (mean (SD)) 9.60 (13.92) <0.001
## EDUC_CAT (%) 387 (15.3) <0.001
## 354 (14.0)
## 876 (34.7)
## 411 (16.3)
## 499 (19.7)
## SIZE_CAT (%) 1239 (49.0) <0.001
## 346 (13.7)
## 261 (10.3)
## 681 (26.9)
#Create follow-up time
d$start <- d$EXAM_YR + d$EXAM_MO / 12
d$end <- ifelse(d$DEATH == 1,
d$DIE_YR + d$DIE_MO / 12,
d$LAST_YR + d$LAST_MO / 12)
d$FU <- d$end - d$start
#Adjusted Cox regression with SEX
cox <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + SEX +
as.factor(RACE) + as.factor(GRADES) + as.factor(MARRY) + BMI +
AVGSMK + SIZE, data = d, ties='efron')
summary(cox)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + SEX +
## as.factor(RACE) + as.factor(GRADES) + as.factor(MARRY) +
## BMI + AVGSMK + SIZE, data = d, ties = "efron")
##
## n= 9250, number of events= 2145
##
## coef exp(coef) se(coef) z Pr(>|z|)
## as.factor(BOOZE_q)0–0.5/week -0.131786 0.876529 0.075867 -1.737 0.082376 .
## as.factor(BOOZE_q)0.5–2/week -0.390542 0.676690 0.065568 -5.956 2.58e-09 ***
## as.factor(BOOZE_q)>2/week -0.333146 0.716665 0.058474 -5.697 1.22e-08 ***
## SEX -0.773141 0.461561 0.049172 -15.723 < 2e-16 ***
## as.factor(RACE)2 -0.265985 0.766450 0.075590 -3.519 0.000434 ***
## as.factor(RACE)3 -0.513794 0.598222 0.198879 -2.583 0.009782 **
## as.factor(GRADES)1 0.599987 1.822095 0.314018 1.911 0.056046 .
## as.factor(GRADES)2 0.520093 1.682184 0.295838 1.758 0.078742 .
## as.factor(GRADES)3 0.701697 2.017172 0.252651 2.777 0.005481 **
## as.factor(GRADES)4 0.668808 1.951909 0.244717 2.733 0.006276 **
## as.factor(GRADES)5 0.707530 2.028973 0.250421 2.825 0.004723 **
## as.factor(GRADES)6 0.344214 1.410881 0.236150 1.458 0.144949
## as.factor(GRADES)7 0.391113 1.478625 0.237484 1.647 0.099578 .
## as.factor(GRADES)8 0.524292 1.689263 0.220388 2.379 0.017362 *
## as.factor(GRADES)9 0.393780 1.482575 0.230085 1.711 0.086997 .
## as.factor(GRADES)10 0.177886 1.194689 0.228746 0.778 0.436771
## as.factor(GRADES)11 0.214700 1.239490 0.235460 0.912 0.361857
## as.factor(GRADES)12 -0.033569 0.966988 0.218656 -0.154 0.877984
## as.factor(GRADES)13 -0.132898 0.875555 0.243908 -0.545 0.585843
## as.factor(GRADES)14 -0.214628 0.806841 0.241954 -0.887 0.375046
## as.factor(GRADES)15 -0.177631 0.837251 0.272086 -0.653 0.513853
## as.factor(GRADES)16 -0.170102 0.843579 0.237427 -0.716 0.473721
## as.factor(GRADES)17 -0.615065 0.540606 0.248169 -2.478 0.013197 *
## as.factor(MARRY)3 0.708942 2.031840 0.062116 11.413 < 2e-16 ***
## as.factor(MARRY)4 0.065615 1.067815 0.101914 0.644 0.519686
## as.factor(MARRY)5 0.030171 1.030631 0.144768 0.208 0.834910
## as.factor(MARRY)6 0.156516 1.169430 0.096475 1.622 0.104728
## as.factor(MARRY)8 0.746167 2.108901 0.336343 2.218 0.026523 *
## BMI -0.013787 0.986307 0.004682 -2.945 0.003232 **
## AVGSMK 0.004971 1.004984 0.001629 3.051 0.002279 **
## SIZE -0.022890 0.977370 0.008506 -2.691 0.007120 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week 0.8765 1.1409 0.7554 1.0171
## as.factor(BOOZE_q)0.5–2/week 0.6767 1.4778 0.5951 0.7695
## as.factor(BOOZE_q)>2/week 0.7167 1.3954 0.6391 0.8037
## SEX 0.4616 2.1666 0.4192 0.5083
## as.factor(RACE)2 0.7665 1.3047 0.6609 0.8888
## as.factor(RACE)3 0.5982 1.6716 0.4051 0.8834
## as.factor(GRADES)1 1.8221 0.5488 0.9846 3.3718
## as.factor(GRADES)2 1.6822 0.5945 0.9420 3.0039
## as.factor(GRADES)3 2.0172 0.4957 1.2294 3.3098
## as.factor(GRADES)4 1.9519 0.5123 1.2082 3.1533
## as.factor(GRADES)5 2.0290 0.4929 1.2420 3.3146
## as.factor(GRADES)6 1.4109 0.7088 0.8881 2.2413
## as.factor(GRADES)7 1.4786 0.6763 0.9283 2.3551
## as.factor(GRADES)8 1.6893 0.5920 1.0967 2.6019
## as.factor(GRADES)9 1.4826 0.6745 0.9444 2.3274
## as.factor(GRADES)10 1.1947 0.8370 0.7630 1.8705
## as.factor(GRADES)11 1.2395 0.8068 0.7813 1.9664
## as.factor(GRADES)12 0.9670 1.0341 0.6299 1.4844
## as.factor(GRADES)13 0.8756 1.1421 0.5428 1.4122
## as.factor(GRADES)14 0.8068 1.2394 0.5022 1.2964
## as.factor(GRADES)15 0.8373 1.1944 0.4912 1.4271
## as.factor(GRADES)16 0.8436 1.1854 0.5297 1.3435
## as.factor(GRADES)17 0.5406 1.8498 0.3324 0.8793
## as.factor(MARRY)3 2.0318 0.4922 1.7989 2.2949
## as.factor(MARRY)4 1.0678 0.9365 0.8745 1.3039
## as.factor(MARRY)5 1.0306 0.9703 0.7760 1.3688
## as.factor(MARRY)6 1.1694 0.8551 0.9680 1.4128
## as.factor(MARRY)8 2.1089 0.4742 1.0908 4.0771
## BMI 0.9863 1.0139 0.9773 0.9954
## AVGSMK 1.0050 0.9950 1.0018 1.0082
## SIZE 0.9774 1.0232 0.9612 0.9938
##
## Concordance= 0.661 (se = 0.006 )
## Likelihood ratio test= 651 on 31 df, p=<2e-16
## Wald test = 649.1 on 31 df, p=<2e-16
## Score (logrank) test = 673.9 on 31 df, p=<2e-16
cox.zph(cox)
## chisq df p
## as.factor(BOOZE_q) 7.813 3 0.05004
## SEX 11.185 1 0.00082
## as.factor(RACE) 1.933 2 0.38039
## as.factor(GRADES) 20.679 17 0.24099
## as.factor(MARRY) 4.452 5 0.48634
## BMI 0.173 1 0.67753
## AVGSMK 0.458 1 0.49844
## SIZE 0.264 1 0.60707
## GLOBAL 48.114 31 0.02566
plot(cox.zph(cox))
#Product term with SEX Cox regression
cox_product <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q)*SEX +
as.factor(RACE) + as.factor(GRADES) + as.factor(MARRY) +
BMI + AVGSMK + SIZE, data = d, ties = "efron")
summary(cox_product)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) * SEX +
## as.factor(RACE) + as.factor(GRADES) + as.factor(MARRY) +
## BMI + AVGSMK + SIZE, data = d, ties = "efron")
##
## n= 9250, number of events= 2145
##
## coef exp(coef) se(coef) z Pr(>|z|)
## as.factor(BOOZE_q)0–0.5/week -0.161405 0.850947 0.236705 -0.682 0.495313
## as.factor(BOOZE_q)0.5–2/week -0.453902 0.635145 0.194085 -2.339 0.019352
## as.factor(BOOZE_q)>2/week -0.567586 0.566892 0.166506 -3.409 0.000653
## SEX -0.817512 0.441529 0.064487 -12.677 < 2e-16
## as.factor(RACE)2 -0.266209 0.766279 0.075599 -3.521 0.000429
## as.factor(RACE)3 -0.511089 0.599842 0.198899 -2.570 0.010182
## as.factor(GRADES)1 0.597777 1.818073 0.314051 1.903 0.056983
## as.factor(GRADES)2 0.516572 1.676272 0.295965 1.745 0.080919
## as.factor(GRADES)3 0.705668 2.025200 0.252666 2.793 0.005224
## as.factor(GRADES)4 0.674080 1.962227 0.244765 2.754 0.005887
## as.factor(GRADES)5 0.712374 2.038825 0.250470 2.844 0.004453
## as.factor(GRADES)6 0.347922 1.416121 0.236162 1.473 0.140688
## as.factor(GRADES)7 0.394282 1.483318 0.237521 1.660 0.096917
## as.factor(GRADES)8 0.527903 1.695374 0.220403 2.395 0.016612
## as.factor(GRADES)9 0.394902 1.484239 0.230093 1.716 0.086112
## as.factor(GRADES)10 0.181665 1.199212 0.228753 0.794 0.427108
## as.factor(GRADES)11 0.217739 1.243262 0.235479 0.925 0.355141
## as.factor(GRADES)12 -0.032482 0.968040 0.218671 -0.149 0.881915
## as.factor(GRADES)13 -0.134216 0.874401 0.243941 -0.550 0.582183
## as.factor(GRADES)14 -0.216948 0.804972 0.241980 -0.897 0.369958
## as.factor(GRADES)15 -0.178067 0.836886 0.272107 -0.654 0.512854
## as.factor(GRADES)16 -0.168185 0.845198 0.237443 -0.708 0.478749
## as.factor(GRADES)17 -0.613072 0.541684 0.248185 -2.470 0.013503
## as.factor(MARRY)3 0.713826 2.041788 0.062203 11.476 < 2e-16
## as.factor(MARRY)4 0.063219 1.065260 0.101959 0.620 0.535231
## as.factor(MARRY)5 0.032512 1.033046 0.144813 0.225 0.822363
## as.factor(MARRY)6 0.158054 1.171229 0.096484 1.638 0.101392
## as.factor(MARRY)8 0.747464 2.111638 0.336519 2.221 0.026340
## BMI -0.013141 0.986945 0.004706 -2.793 0.005227
## AVGSMK 0.004964 1.004976 0.001629 3.046 0.002316
## SIZE -0.022786 0.977472 0.008512 -2.677 0.007428
## as.factor(BOOZE_q)0–0.5/week:SEX 0.019546 1.019738 0.150620 0.130 0.896748
## as.factor(BOOZE_q)0.5–2/week:SEX 0.042411 1.043323 0.131314 0.323 0.746717
## as.factor(BOOZE_q)>2/week:SEX 0.183497 1.201412 0.120545 1.522 0.127949
##
## as.factor(BOOZE_q)0–0.5/week
## as.factor(BOOZE_q)0.5–2/week *
## as.factor(BOOZE_q)>2/week ***
## SEX ***
## as.factor(RACE)2 ***
## as.factor(RACE)3 *
## as.factor(GRADES)1 .
## as.factor(GRADES)2 .
## as.factor(GRADES)3 **
## as.factor(GRADES)4 **
## as.factor(GRADES)5 **
## as.factor(GRADES)6
## as.factor(GRADES)7 .
## as.factor(GRADES)8 *
## as.factor(GRADES)9 .
## as.factor(GRADES)10
## as.factor(GRADES)11
## as.factor(GRADES)12
## as.factor(GRADES)13
## as.factor(GRADES)14
## as.factor(GRADES)15
## as.factor(GRADES)16
## as.factor(GRADES)17 *
## as.factor(MARRY)3 ***
## as.factor(MARRY)4
## as.factor(MARRY)5
## as.factor(MARRY)6
## as.factor(MARRY)8 *
## BMI **
## AVGSMK **
## SIZE **
## as.factor(BOOZE_q)0–0.5/week:SEX
## as.factor(BOOZE_q)0.5–2/week:SEX
## as.factor(BOOZE_q)>2/week:SEX
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week 0.8509 1.1752 0.5351 1.3533
## as.factor(BOOZE_q)0.5–2/week 0.6351 1.5744 0.4342 0.9291
## as.factor(BOOZE_q)>2/week 0.5669 1.7640 0.4090 0.7857
## SEX 0.4415 2.2649 0.3891 0.5010
## as.factor(RACE)2 0.7663 1.3050 0.6607 0.8887
## as.factor(RACE)3 0.5998 1.6671 0.4062 0.8858
## as.factor(GRADES)1 1.8181 0.5500 0.9824 3.3646
## as.factor(GRADES)2 1.6763 0.5966 0.9385 2.9941
## as.factor(GRADES)3 2.0252 0.4938 1.2342 3.3231
## as.factor(GRADES)4 1.9622 0.5096 1.2145 3.1703
## as.factor(GRADES)5 2.0388 0.4905 1.2479 3.3310
## as.factor(GRADES)6 1.4161 0.7062 0.8914 2.2497
## as.factor(GRADES)7 1.4833 0.6742 0.9312 2.3627
## as.factor(GRADES)8 1.6954 0.5898 1.1007 2.6114
## as.factor(GRADES)9 1.4842 0.6737 0.9455 2.3300
## as.factor(GRADES)10 1.1992 0.8339 0.7659 1.8776
## as.factor(GRADES)11 1.2433 0.8043 0.7837 1.9724
## as.factor(GRADES)12 0.9680 1.0330 0.6306 1.4860
## as.factor(GRADES)13 0.8744 1.1436 0.5421 1.4104
## as.factor(GRADES)14 0.8050 1.2423 0.5010 1.2935
## as.factor(GRADES)15 0.8369 1.1949 0.4910 1.4265
## as.factor(GRADES)16 0.8452 1.1832 0.5307 1.3461
## as.factor(GRADES)17 0.5417 1.8461 0.3330 0.8811
## as.factor(MARRY)3 2.0418 0.4898 1.8074 2.3065
## as.factor(MARRY)4 1.0653 0.9387 0.8723 1.3009
## as.factor(MARRY)5 1.0330 0.9680 0.7778 1.3721
## as.factor(MARRY)6 1.1712 0.8538 0.9694 1.4150
## as.factor(MARRY)8 2.1116 0.4736 1.0919 4.0838
## BMI 0.9869 1.0132 0.9779 0.9961
## AVGSMK 1.0050 0.9950 1.0018 1.0082
## SIZE 0.9775 1.0230 0.9613 0.9939
## as.factor(BOOZE_q)0–0.5/week:SEX 1.0197 0.9806 0.7591 1.3699
## as.factor(BOOZE_q)0.5–2/week:SEX 1.0433 0.9585 0.8066 1.3496
## as.factor(BOOZE_q)>2/week:SEX 1.2014 0.8324 0.9486 1.5216
##
## Concordance= 0.661 (se = 0.006 )
## Likelihood ratio test= 653.3 on 34 df, p=<2e-16
## Wald test = 658.5 on 34 df, p=<2e-16
## Score (logrank) test = 694.2 on 34 df, p=<2e-16
cox.zph(cox_product)
## chisq df p
## as.factor(BOOZE_q) 7.669 3 0.05337
## SEX 11.045 1 0.00089
## as.factor(RACE) 1.948 2 0.37762
## as.factor(GRADES) 20.607 17 0.24437
## as.factor(MARRY) 4.475 5 0.48325
## BMI 0.172 1 0.67826
## AVGSMK 0.472 1 0.49207
## SIZE 0.253 1 0.61527
## as.factor(BOOZE_q):SEX 12.584 3 0.00563
## GLOBAL 47.959 34 0.05671
plot(cox.zph(cox_product))
#Kaplan
fit<-survfit(Surv(FU, DEATH)~BOOZE_q, data=d)
summary(fit)
## Call: survfit(formula = Surv(FU, DEATH) ~ BOOZE_q, data = d)
##
## BOOZE_q=0/week
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0000 4053 2 1.000 0.000349 0.999 1.000
## 0.0833 4051 3 0.999 0.000551 0.998 1.000
## 0.1667 4048 1 0.999 0.000604 0.997 1.000
## 0.2500 4047 4 0.998 0.000779 0.996 0.999
## 0.3333 4043 6 0.996 0.000985 0.994 0.998
## 0.4167 4037 2 0.996 0.001044 0.994 0.998
## 0.5000 4035 2 0.995 0.001101 0.993 0.997
## 0.5833 4033 7 0.993 0.001278 0.991 0.996
## 0.6667 4026 3 0.993 0.001346 0.990 0.995
## 0.7500 4023 3 0.992 0.001412 0.989 0.995
## 0.8333 4020 4 0.991 0.001494 0.988 0.994
## 0.9167 4016 1 0.991 0.001514 0.988 0.994
## 1.0000 4015 6 0.989 0.001628 0.986 0.992
## 1.0833 4009 5 0.988 0.001717 0.985 0.991
## 1.1667 4004 5 0.987 0.001801 0.983 0.990
## 1.2500 3999 5 0.985 0.001881 0.982 0.989
## 1.3333 3994 4 0.984 0.001943 0.981 0.988
## 1.4167 3990 4 0.983 0.002003 0.980 0.987
## 1.5000 3986 6 0.982 0.002089 0.978 0.986
## 1.5833 3980 4 0.981 0.002144 0.977 0.985
## 1.6667 3976 6 0.980 0.002225 0.975 0.984
## 1.7500 3970 10 0.977 0.002352 0.972 0.982
## 1.8333 3960 7 0.975 0.002437 0.971 0.980
## 1.9167 3953 6 0.974 0.002507 0.969 0.979
## 2.0000 3947 4 0.973 0.002552 0.968 0.978
## 2.0833 3943 4 0.972 0.002597 0.967 0.977
## 2.1667 3939 1 0.972 0.002608 0.967 0.977
## 2.2500 3938 7 0.970 0.002684 0.965 0.975
## 2.3333 3931 3 0.969 0.002716 0.964 0.974
## 2.4167 3928 7 0.967 0.002788 0.962 0.973
## 2.5000 3921 11 0.965 0.002898 0.959 0.970
## 2.5833 3910 8 0.963 0.002975 0.957 0.969
## 2.6667 3902 8 0.961 0.003050 0.955 0.967
## 2.7500 3894 2 0.960 0.003068 0.954 0.966
## 2.8333 3892 2 0.960 0.003086 0.954 0.966
## 2.9167 3890 7 0.958 0.003149 0.952 0.964
## 3.0000 3883 10 0.956 0.003236 0.949 0.962
## 3.0833 3873 6 0.954 0.003287 0.948 0.961
## 3.1667 3867 5 0.953 0.003329 0.946 0.959
## 3.2500 3862 6 0.951 0.003378 0.945 0.958
## 3.3333 3856 1 0.951 0.003386 0.945 0.958
## 3.4167 3855 6 0.950 0.003434 0.943 0.956
## 3.5000 3849 1 0.949 0.003442 0.943 0.956
## 3.5833 3848 5 0.948 0.003482 0.941 0.955
## 3.6667 3843 8 0.946 0.003544 0.939 0.953
## 3.7500 3835 10 0.944 0.003619 0.937 0.951
## 3.8333 3825 1 0.943 0.003627 0.936 0.951
## 3.9167 3824 6 0.942 0.003671 0.935 0.949
## 4.0000 3818 10 0.940 0.003743 0.932 0.947
## 4.0833 3808 8 0.938 0.003800 0.930 0.945
## 4.1667 3800 1 0.937 0.003807 0.930 0.945
## 4.2500 3799 3 0.937 0.003828 0.929 0.944
## 4.3333 3796 5 0.935 0.003862 0.928 0.943
## 4.4167 3791 4 0.934 0.003890 0.927 0.942
## 4.5000 3787 4 0.933 0.003917 0.926 0.941
## 4.5833 3783 5 0.932 0.003950 0.924 0.940
## 4.6667 3778 7 0.930 0.003997 0.923 0.938
## 4.7500 3771 5 0.929 0.004029 0.921 0.937
## 4.8333 3766 7 0.927 0.004074 0.920 0.935
## 4.9167 3759 9 0.925 0.004131 0.917 0.933
## 5.0000 3750 4 0.924 0.004156 0.916 0.932
## 5.0833 3746 6 0.923 0.004193 0.915 0.931
## 5.1667 3740 7 0.921 0.004236 0.913 0.929
## 5.2500 3733 5 0.920 0.004266 0.911 0.928
## 5.3333 3728 5 0.919 0.004296 0.910 0.927
## 5.4167 3723 7 0.917 0.004337 0.908 0.925
## 5.5000 3716 8 0.915 0.004383 0.906 0.924
## 5.5833 3708 6 0.913 0.004418 0.905 0.922
## 5.6667 3702 9 0.911 0.004469 0.902 0.920
## 5.7500 3693 9 0.909 0.004519 0.900 0.918
## 5.8333 3684 9 0.907 0.004568 0.898 0.916
## 5.9167 3675 8 0.905 0.004611 0.896 0.914
## 6.0000 3667 10 0.902 0.004664 0.893 0.911
## 6.0833 3657 6 0.901 0.004695 0.892 0.910
## 6.1667 3651 4 0.900 0.004716 0.891 0.909
## 6.2500 3647 4 0.899 0.004736 0.890 0.908
## 6.3333 3643 6 0.897 0.004767 0.888 0.907
## 6.4167 3637 6 0.896 0.004797 0.887 0.905
## 6.5000 3631 4 0.895 0.004817 0.886 0.904
## 6.5833 3627 6 0.893 0.004847 0.884 0.903
## 6.6667 3621 10 0.891 0.004896 0.881 0.901
## 6.7500 3611 5 0.890 0.004920 0.880 0.899
## 6.8333 3606 9 0.887 0.004963 0.878 0.897
## 6.9167 3597 7 0.886 0.004997 0.876 0.896
## 7.0000 3590 4 0.885 0.005015 0.875 0.895
## 7.0833 3586 7 0.883 0.005048 0.873 0.893
## 7.1667 3579 7 0.881 0.005080 0.871 0.891
## 7.2500 3572 3 0.881 0.005094 0.871 0.891
## 7.3333 3569 7 0.879 0.005125 0.869 0.889
## 7.4167 3562 1 0.879 0.005130 0.869 0.889
## 7.5000 3561 11 0.876 0.005179 0.866 0.886
## 7.5833 3550 8 0.874 0.005214 0.864 0.884
## 7.6667 3542 9 0.872 0.005253 0.861 0.882
## 7.7500 3533 7 0.870 0.005283 0.860 0.880
## 7.8333 3526 6 0.868 0.005308 0.858 0.879
## 7.9167 3520 10 0.866 0.005350 0.856 0.877
## 8.0000 3510 7 0.864 0.005379 0.854 0.875
## 8.0833 3503 3 0.864 0.005392 0.853 0.874
## 8.1667 3500 8 0.862 0.005424 0.851 0.872
## 8.2500 3492 5 0.860 0.005445 0.850 0.871
## 8.3333 3487 5 0.859 0.005465 0.848 0.870
## 8.4167 3482 9 0.857 0.005500 0.846 0.868
## 8.5000 3473 7 0.855 0.005528 0.844 0.866
## 8.5833 3466 9 0.853 0.005563 0.842 0.864
## 8.6667 3457 6 0.851 0.005586 0.841 0.862
## 8.7500 3451 4 0.850 0.005601 0.840 0.862
## 8.8333 3447 4 0.849 0.005617 0.839 0.861
## 8.9167 3443 8 0.848 0.005647 0.837 0.859
## 9.0000 3435 6 0.846 0.005669 0.835 0.857
## 9.0833 3429 3 0.845 0.005680 0.834 0.857
## 9.1667 3426 10 0.843 0.005717 0.832 0.854
## 9.2500 3416 2 0.842 0.005724 0.831 0.854
## 9.3333 3414 4 0.841 0.005739 0.830 0.853
## 9.4167 3410 4 0.840 0.005753 0.829 0.852
## 9.5000 3406 4 0.839 0.005768 0.828 0.851
## 9.5833 3402 8 0.837 0.005796 0.826 0.849
## 9.6667 3394 8 0.835 0.005824 0.824 0.847
## 9.7500 3386 4 0.834 0.005838 0.823 0.846
## 9.8333 3382 10 0.832 0.005873 0.821 0.844
## 9.9167 3372 5 0.831 0.005890 0.819 0.842
## 10.0000 3367 8 0.829 0.005917 0.817 0.840
## 10.0833 3359 8 0.827 0.005944 0.815 0.839
## 10.1667 3351 11 0.824 0.005981 0.812 0.836
## 10.2500 3340 3 0.823 0.005991 0.812 0.835
## 10.3333 3337 10 0.821 0.006023 0.809 0.833
## 10.4167 3327 8 0.819 0.006049 0.807 0.831
## 10.5000 3319 6 0.817 0.006068 0.806 0.829
## 10.5833 3313 4 0.816 0.006081 0.805 0.828
## 10.6667 3309 7 0.815 0.006103 0.803 0.827
## 10.7500 3302 8 0.813 0.006128 0.801 0.825
## 10.8333 3294 5 0.811 0.006143 0.800 0.824
## 10.9167 3289 8 0.810 0.006168 0.798 0.822
## 11.0000 3281 6 0.808 0.006186 0.796 0.820
## 11.0833 3275 5 0.807 0.006201 0.795 0.819
## 11.1667 3270 6 0.805 0.006219 0.793 0.818
## 11.2500 3264 5 0.804 0.006234 0.792 0.816
## 11.3333 3259 12 0.801 0.006270 0.789 0.814
## 11.4167 3247 5 0.800 0.006284 0.788 0.812
## 11.5000 3242 10 0.797 0.006313 0.785 0.810
## 11.5833 3232 9 0.795 0.006339 0.783 0.808
## 11.6667 3223 9 0.793 0.006364 0.781 0.806
## 11.7500 3214 5 0.792 0.006378 0.779 0.804
## 11.8333 3209 5 0.791 0.006392 0.778 0.803
## 11.9167 3204 7 0.789 0.006411 0.776 0.801
## 12.0000 3197 6 0.787 0.006428 0.775 0.800
## 12.0833 3191 8 0.785 0.006449 0.773 0.798
## 12.1667 3183 7 0.784 0.006468 0.771 0.796
## 12.2500 3176 3 0.783 0.006476 0.770 0.796
## 12.3333 3173 9 0.781 0.006500 0.768 0.794
## 12.4167 3164 7 0.779 0.006518 0.766 0.792
## 12.5000 3157 9 0.777 0.006541 0.764 0.790
## 12.5833 3148 9 0.774 0.006565 0.762 0.787
## 12.6667 3139 3 0.774 0.006572 0.761 0.787
## 12.7500 3136 8 0.772 0.006592 0.759 0.785
## 12.8333 3128 6 0.770 0.006607 0.757 0.783
## 12.9167 3032 6 0.769 0.006624 0.756 0.782
## 13.0000 2965 9 0.766 0.006649 0.754 0.780
## 13.0833 2935 5 0.765 0.006663 0.752 0.778
## 13.1667 2849 4 0.764 0.006675 0.751 0.777
## 13.2500 2773 4 0.763 0.006689 0.750 0.776
## 13.3333 2688 6 0.761 0.006710 0.748 0.775
## 13.4167 2583 4 0.760 0.006725 0.747 0.773
## 13.5000 2578 6 0.758 0.006748 0.745 0.772
## 13.5833 2503 3 0.757 0.006760 0.744 0.771
## 13.6667 2438 7 0.755 0.006791 0.742 0.769
## 13.7500 2342 5 0.754 0.006814 0.740 0.767
## 13.8333 2194 5 0.752 0.006842 0.739 0.765
## 13.9167 2115 3 0.751 0.006860 0.737 0.764
## 14.0000 2062 1 0.750 0.006866 0.737 0.764
## 14.0833 2048 2 0.750 0.006879 0.736 0.763
## 14.1667 2009 1 0.749 0.006886 0.736 0.763
## 14.2500 1965 6 0.747 0.006928 0.734 0.761
## 14.3333 1926 6 0.745 0.006971 0.731 0.759
## 14.4167 1857 2 0.744 0.006987 0.730 0.758
## 14.5000 1806 6 0.741 0.007036 0.728 0.755
## 14.5833 1700 2 0.741 0.007055 0.727 0.755
## 14.6667 1617 4 0.739 0.007096 0.725 0.753
## 14.7500 1518 2 0.738 0.007120 0.724 0.752
## 14.8333 1456 2 0.737 0.007147 0.723 0.751
## 14.9167 1425 1 0.736 0.007160 0.722 0.750
## 15.0000 1397 4 0.734 0.007217 0.720 0.748
## 15.0833 1340 3 0.733 0.007263 0.718 0.747
## 15.1667 1291 2 0.731 0.007296 0.717 0.746
## 15.2500 1262 1 0.731 0.007313 0.717 0.745
## 15.3333 1228 5 0.728 0.007403 0.713 0.742
## 15.4167 1178 3 0.726 0.007461 0.711 0.741
## 15.5000 1145 2 0.725 0.007502 0.710 0.740
## 15.5833 1114 2 0.723 0.007545 0.709 0.738
## 15.6667 1079 2 0.722 0.007590 0.707 0.737
## 15.7500 1018 1 0.721 0.007616 0.707 0.736
## 15.8333 860 1 0.721 0.007653 0.706 0.736
## 15.9167 803 3 0.718 0.007781 0.703 0.733
## 16.0000 770 2 0.716 0.007871 0.701 0.732
## 16.0833 670 1 0.715 0.007932 0.699 0.731
## 16.2500 548 1 0.714 0.008024 0.698 0.729
## 16.3333 512 3 0.709 0.008332 0.693 0.726
## 16.5833 220 1 0.706 0.008896 0.689 0.724
##
## BOOZE_q=0–0.5/week
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0000 941 1 0.999 0.00106 0.997 1.000
## 0.0833 940 2 0.997 0.00184 0.993 1.000
## 0.2500 938 1 0.996 0.00212 0.992 1.000
## 0.3333 937 1 0.995 0.00237 0.990 0.999
## 0.5000 936 1 0.994 0.00259 0.989 0.999
## 0.5833 935 2 0.991 0.00299 0.986 0.997
## 0.6667 933 1 0.990 0.00317 0.984 0.997
## 0.8333 932 1 0.989 0.00334 0.983 0.996
## 0.9167 931 1 0.988 0.00350 0.981 0.995
## 1.1667 930 2 0.986 0.00381 0.979 0.994
## 1.2500 928 1 0.985 0.00395 0.977 0.993
## 1.3333 927 1 0.984 0.00408 0.976 0.992
## 1.4167 926 1 0.983 0.00421 0.975 0.991
## 1.5000 925 2 0.981 0.00447 0.972 0.990
## 1.7500 923 2 0.979 0.00470 0.970 0.988
## 1.8333 921 1 0.978 0.00482 0.968 0.987
## 2.0000 920 1 0.977 0.00493 0.967 0.986
## 2.0833 919 1 0.976 0.00503 0.966 0.985
## 2.1667 918 1 0.974 0.00514 0.964 0.985
## 2.2500 917 2 0.972 0.00534 0.962 0.983
## 2.3333 915 1 0.971 0.00544 0.961 0.982
## 2.4167 914 1 0.970 0.00554 0.959 0.981
## 2.5000 913 1 0.969 0.00563 0.958 0.980
## 2.5833 912 1 0.968 0.00573 0.957 0.979
## 2.6667 911 2 0.966 0.00591 0.954 0.978
## 2.7500 909 2 0.964 0.00608 0.952 0.976
## 2.8333 907 2 0.962 0.00625 0.950 0.974
## 2.9167 905 1 0.961 0.00634 0.948 0.973
## 3.0000 904 1 0.960 0.00642 0.947 0.972
## 3.0833 903 1 0.959 0.00650 0.946 0.971
## 3.2500 902 3 0.955 0.00673 0.942 0.969
## 3.3333 899 2 0.953 0.00688 0.940 0.967
## 3.5000 897 1 0.952 0.00696 0.939 0.966
## 3.6667 896 2 0.950 0.00710 0.936 0.964
## 3.7500 894 3 0.947 0.00731 0.933 0.961
## 3.8333 891 1 0.946 0.00738 0.931 0.960
## 4.0000 890 1 0.945 0.00745 0.930 0.959
## 4.0833 889 1 0.944 0.00752 0.929 0.959
## 4.4167 888 1 0.943 0.00758 0.928 0.958
## 4.5000 887 1 0.942 0.00765 0.927 0.957
## 4.7500 886 3 0.938 0.00784 0.923 0.954
## 4.9167 883 1 0.937 0.00790 0.922 0.953
## 5.0000 882 1 0.936 0.00796 0.921 0.952
## 5.0833 881 2 0.934 0.00809 0.918 0.950
## 5.3333 879 2 0.932 0.00821 0.916 0.948
## 5.4167 877 1 0.931 0.00827 0.915 0.947
## 5.5833 876 1 0.930 0.00833 0.914 0.946
## 5.6667 875 1 0.929 0.00838 0.913 0.945
## 5.7500 874 2 0.927 0.00850 0.910 0.943
## 5.8333 872 1 0.926 0.00855 0.909 0.943
## 5.9167 871 1 0.925 0.00861 0.908 0.942
## 6.1667 870 4 0.920 0.00883 0.903 0.938
## 6.2500 866 1 0.919 0.00888 0.902 0.937
## 6.3333 865 2 0.917 0.00899 0.900 0.935
## 6.5000 863 1 0.916 0.00904 0.898 0.934
## 6.5833 862 3 0.913 0.00919 0.895 0.931
## 6.6667 859 1 0.912 0.00924 0.894 0.930
## 7.0833 858 1 0.911 0.00929 0.893 0.929
## 7.1667 857 1 0.910 0.00934 0.892 0.928
## 7.2500 856 1 0.909 0.00939 0.890 0.927
## 7.3333 855 2 0.906 0.00949 0.888 0.925
## 7.5000 853 2 0.904 0.00959 0.886 0.923
## 7.5833 851 2 0.902 0.00968 0.883 0.921
## 7.7500 849 1 0.901 0.00973 0.882 0.920
## 7.8333 848 1 0.900 0.00978 0.881 0.919
## 8.0000 847 2 0.898 0.00987 0.879 0.918
## 8.0833 845 2 0.896 0.00996 0.877 0.916
## 8.1667 843 2 0.894 0.01005 0.874 0.914
## 8.3333 841 1 0.893 0.01009 0.873 0.913
## 8.4167 840 1 0.892 0.01013 0.872 0.912
## 8.5000 839 2 0.889 0.01022 0.870 0.910
## 8.5833 837 1 0.888 0.01026 0.869 0.909
## 8.6667 836 3 0.885 0.01039 0.865 0.906
## 8.7500 833 2 0.883 0.01047 0.863 0.904
## 8.8333 831 2 0.881 0.01056 0.861 0.902
## 8.9167 829 1 0.880 0.01060 0.859 0.901
## 9.0000 828 3 0.877 0.01072 0.856 0.898
## 9.0833 825 1 0.876 0.01076 0.855 0.897
## 9.3333 824 1 0.875 0.01080 0.854 0.896
## 9.4167 823 1 0.874 0.01083 0.853 0.895
## 9.5833 822 2 0.871 0.01091 0.850 0.893
## 9.6667 820 3 0.868 0.01103 0.847 0.890
## 9.7500 817 3 0.865 0.01114 0.843 0.887
## 9.8333 814 1 0.864 0.01118 0.842 0.886
## 10.0833 813 1 0.863 0.01121 0.841 0.885
## 10.2500 812 4 0.859 0.01136 0.837 0.881
## 10.5833 808 2 0.857 0.01143 0.834 0.879
## 10.6667 806 2 0.854 0.01150 0.832 0.877
## 10.7500 804 2 0.852 0.01157 0.830 0.875
## 10.9167 802 3 0.849 0.01167 0.827 0.872
## 11.0000 799 2 0.847 0.01174 0.824 0.870
## 11.0833 797 1 0.846 0.01177 0.823 0.869
## 11.1667 796 1 0.845 0.01180 0.822 0.868
## 11.2500 795 2 0.843 0.01187 0.820 0.866
## 11.3333 793 1 0.842 0.01190 0.819 0.865
## 11.4167 792 2 0.840 0.01197 0.816 0.863
## 11.5000 790 2 0.837 0.01203 0.814 0.861
## 11.5833 788 3 0.834 0.01212 0.811 0.858
## 11.6667 785 1 0.833 0.01215 0.810 0.857
## 11.7500 784 1 0.832 0.01218 0.809 0.856
## 11.8333 783 1 0.831 0.01222 0.807 0.855
## 11.9167 782 2 0.829 0.01228 0.805 0.853
## 12.0000 780 1 0.828 0.01231 0.804 0.852
## 12.0833 779 1 0.827 0.01234 0.803 0.851
## 12.1667 778 3 0.824 0.01243 0.800 0.848
## 12.2500 775 2 0.821 0.01248 0.797 0.846
## 12.3333 773 1 0.820 0.01251 0.796 0.845
## 12.4167 772 1 0.819 0.01254 0.795 0.844
## 12.5000 771 1 0.818 0.01257 0.794 0.843
## 12.6667 770 3 0.815 0.01266 0.791 0.840
## 12.7500 767 1 0.814 0.01268 0.790 0.839
## 12.8333 766 1 0.813 0.01271 0.788 0.838
## 13.0833 738 1 0.812 0.01274 0.787 0.837
## 13.1667 718 3 0.808 0.01284 0.784 0.834
## 13.2500 697 1 0.807 0.01287 0.782 0.833
## 13.3333 668 2 0.805 0.01295 0.780 0.831
## 13.4167 642 2 0.802 0.01303 0.777 0.828
## 13.5000 639 1 0.801 0.01307 0.776 0.827
## 13.5833 613 2 0.799 0.01315 0.773 0.825
## 13.6667 591 3 0.794 0.01329 0.769 0.821
## 13.8333 556 2 0.792 0.01340 0.766 0.818
## 14.0000 522 1 0.790 0.01346 0.764 0.817
## 14.0833 515 2 0.787 0.01358 0.761 0.814
## 14.2500 482 5 0.779 0.01392 0.752 0.807
## 14.3333 471 1 0.777 0.01399 0.750 0.805
## 14.4167 442 1 0.775 0.01407 0.748 0.804
## 14.6667 390 2 0.771 0.01427 0.744 0.800
## 15.0000 329 1 0.769 0.01442 0.741 0.798
## 15.2500 283 1 0.766 0.01463 0.738 0.796
## 15.6667 219 1 0.763 0.01497 0.734 0.793
## 15.7500 197 1 0.759 0.01539 0.729 0.790
## 15.9167 173 1 0.755 0.01591 0.724 0.786
## 16.1667 141 1 0.749 0.01668 0.717 0.783
## 16.5833 57 1 0.736 0.02093 0.696 0.778
## 16.6667 45 1 0.720 0.02609 0.670 0.773
##
## BOOZE_q=0.5–2/week
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.0000 1729 1 0.999 0.000578 0.998 1.000
## 0.0833 1728 1 0.999 0.000817 0.997 1.000
## 0.1667 1727 1 0.998 0.001001 0.996 1.000
## 0.3333 1726 1 0.998 0.001155 0.995 1.000
## 0.4167 1725 1 0.997 0.001291 0.995 1.000
## 0.7500 1724 1 0.997 0.001414 0.994 0.999
## 0.8333 1723 1 0.996 0.001527 0.993 0.999
## 1.0000 1722 3 0.994 0.001824 0.991 0.998
## 1.1667 1719 2 0.993 0.001997 0.989 0.997
## 1.2500 1717 3 0.991 0.002230 0.987 0.996
## 1.3333 1714 2 0.990 0.002373 0.986 0.995
## 1.4167 1712 1 0.990 0.002441 0.985 0.994
## 1.5000 1711 1 0.989 0.002507 0.984 0.994
## 1.5833 1710 1 0.988 0.002572 0.983 0.993
## 1.6667 1709 2 0.987 0.002695 0.982 0.993
## 1.7500 1707 2 0.986 0.002814 0.981 0.992
## 1.8333 1705 1 0.986 0.002871 0.980 0.991
## 2.0000 1704 1 0.985 0.002927 0.979 0.991
## 2.0833 1703 2 0.984 0.003036 0.978 0.990
## 2.1667 1701 1 0.983 0.003088 0.977 0.989
## 2.2500 1700 1 0.983 0.003140 0.977 0.989
## 2.3333 1699 1 0.982 0.003191 0.976 0.988
## 2.5000 1698 4 0.980 0.003387 0.973 0.986
## 2.5833 1694 2 0.979 0.003480 0.972 0.985
## 2.6667 1692 2 0.977 0.003571 0.970 0.984
## 2.7500 1690 3 0.976 0.003702 0.968 0.983
## 2.8333 1687 3 0.974 0.003829 0.966 0.982
## 2.9167 1684 4 0.972 0.003991 0.964 0.980
## 3.0000 1680 1 0.971 0.004030 0.963 0.979
## 3.0833 1679 2 0.970 0.004107 0.962 0.978
## 3.1667 1677 2 0.969 0.004183 0.961 0.977
## 3.2500 1675 1 0.968 0.004221 0.960 0.976
## 3.3333 1674 2 0.967 0.004294 0.959 0.975
## 3.4167 1672 2 0.966 0.004366 0.957 0.974
## 3.5000 1670 1 0.965 0.004402 0.957 0.974
## 3.5833 1669 2 0.964 0.004472 0.955 0.973
## 3.6667 1667 3 0.962 0.004574 0.953 0.971
## 3.7500 1664 1 0.962 0.004608 0.953 0.971
## 3.8333 1663 3 0.960 0.004707 0.951 0.969
## 4.0000 1660 5 0.957 0.004868 0.948 0.967
## 4.0833 1655 3 0.955 0.004961 0.946 0.965
## 4.1667 1652 4 0.953 0.005082 0.943 0.963
## 4.2500 1648 1 0.953 0.005112 0.943 0.963
## 4.3333 1647 2 0.951 0.005170 0.941 0.962
## 4.4167 1645 1 0.951 0.005200 0.941 0.961
## 4.5000 1644 1 0.950 0.005228 0.940 0.961
## 4.5833 1643 1 0.950 0.005257 0.939 0.960
## 4.6667 1642 2 0.949 0.005314 0.938 0.959
## 4.7500 1640 2 0.947 0.005370 0.937 0.958
## 4.8333 1638 1 0.947 0.005398 0.936 0.957
## 4.9167 1637 2 0.946 0.005453 0.935 0.956
## 5.0000 1635 2 0.944 0.005507 0.934 0.955
## 5.0833 1633 4 0.942 0.005614 0.931 0.953
## 5.2500 1629 2 0.941 0.005666 0.930 0.952
## 5.4167 1627 2 0.940 0.005718 0.929 0.951
## 5.5000 1625 1 0.939 0.005744 0.928 0.951
## 5.5833 1624 1 0.939 0.005769 0.927 0.950
## 5.6667 1623 1 0.938 0.005795 0.927 0.950
## 5.7500 1622 2 0.937 0.005845 0.926 0.948
## 5.8333 1620 1 0.936 0.005870 0.925 0.948
## 6.0833 1619 2 0.935 0.005919 0.924 0.947
## 6.1667 1617 1 0.935 0.005944 0.923 0.946
## 6.2500 1616 1 0.934 0.005968 0.922 0.946
## 6.4167 1615 3 0.932 0.006041 0.921 0.944
## 6.5000 1612 1 0.932 0.006065 0.920 0.944
## 6.5833 1611 4 0.929 0.006159 0.917 0.942
## 6.6667 1607 3 0.928 0.006228 0.916 0.940
## 6.7500 1604 4 0.925 0.006319 0.913 0.938
## 6.8333 1600 1 0.925 0.006342 0.912 0.937
## 6.9167 1599 1 0.924 0.006364 0.912 0.937
## 7.0000 1598 1 0.924 0.006386 0.911 0.936
## 7.0833 1597 1 0.923 0.006408 0.911 0.936
## 7.1667 1596 1 0.922 0.006430 0.910 0.935
## 7.2500 1595 1 0.922 0.006452 0.909 0.935
## 7.3333 1594 4 0.920 0.006539 0.907 0.933
## 7.4167 1590 1 0.919 0.006560 0.906 0.932
## 7.5000 1589 1 0.918 0.006582 0.906 0.931
## 7.5833 1588 5 0.916 0.006687 0.903 0.929
## 7.6667 1583 6 0.912 0.006810 0.899 0.926
## 7.7500 1577 1 0.912 0.006830 0.898 0.925
## 7.8333 1576 1 0.911 0.006850 0.898 0.924
## 7.9167 1575 1 0.910 0.006870 0.897 0.924
## 8.0000 1574 3 0.909 0.006930 0.895 0.922
## 8.0833 1571 3 0.907 0.006989 0.893 0.921
## 8.1667 1568 4 0.905 0.007066 0.891 0.919
## 8.2500 1564 3 0.903 0.007123 0.889 0.917
## 8.3333 1561 3 0.901 0.007179 0.887 0.915
## 8.4167 1558 2 0.900 0.007217 0.886 0.914
## 8.5000 1556 3 0.898 0.007272 0.884 0.913
## 8.5833 1553 1 0.898 0.007290 0.883 0.912
## 8.6667 1552 1 0.897 0.007308 0.883 0.911
## 8.7500 1551 3 0.895 0.007363 0.881 0.910
## 8.8333 1548 1 0.895 0.007381 0.880 0.909
## 8.9167 1547 2 0.894 0.007416 0.879 0.908
## 9.0000 1545 1 0.893 0.007434 0.879 0.908
## 9.1667 1544 3 0.891 0.007487 0.877 0.906
## 9.4167 1541 1 0.891 0.007504 0.876 0.906
## 9.5000 1540 1 0.890 0.007521 0.875 0.905
## 9.5833 1539 3 0.888 0.007573 0.874 0.903
## 9.6667 1536 1 0.888 0.007590 0.873 0.903
## 9.7500 1535 2 0.887 0.007624 0.872 0.902
## 9.8333 1533 2 0.885 0.007658 0.871 0.901
## 9.9167 1531 2 0.884 0.007692 0.869 0.900
## 10.0000 1529 1 0.884 0.007708 0.869 0.899
## 10.0833 1528 3 0.882 0.007758 0.867 0.897
## 10.1667 1525 3 0.880 0.007807 0.865 0.896
## 10.2500 1522 2 0.879 0.007840 0.864 0.895
## 10.3333 1520 1 0.879 0.007856 0.863 0.894
## 10.4167 1519 4 0.876 0.007920 0.861 0.892
## 10.5000 1515 3 0.874 0.007967 0.859 0.890
## 10.5833 1512 5 0.872 0.008045 0.856 0.888
## 10.6667 1507 1 0.871 0.008061 0.855 0.887
## 10.7500 1506 1 0.870 0.008076 0.855 0.886
## 10.8333 1505 2 0.869 0.008107 0.854 0.885
## 10.9167 1503 2 0.868 0.008137 0.852 0.884
## 11.0000 1501 2 0.867 0.008167 0.851 0.883
## 11.1667 1499 1 0.866 0.008182 0.851 0.883
## 11.2500 1498 2 0.865 0.008212 0.849 0.881
## 11.3333 1496 2 0.864 0.008242 0.848 0.880
## 11.4167 1494 1 0.864 0.008256 0.847 0.880
## 11.5000 1493 3 0.862 0.008300 0.846 0.878
## 11.5833 1490 3 0.860 0.008344 0.844 0.877
## 11.6667 1487 2 0.859 0.008373 0.843 0.875
## 11.7500 1485 2 0.858 0.008401 0.841 0.874
## 11.8333 1483 3 0.856 0.008444 0.840 0.873
## 11.9167 1480 2 0.855 0.008472 0.838 0.872
## 12.0000 1478 2 0.854 0.008500 0.837 0.870
## 12.1667 1476 4 0.851 0.008555 0.835 0.868
## 12.2500 1472 3 0.850 0.008596 0.833 0.867
## 12.3333 1469 3 0.848 0.008637 0.831 0.865
## 12.4167 1466 3 0.846 0.008677 0.829 0.863
## 12.5000 1463 1 0.846 0.008690 0.829 0.863
## 12.6667 1462 2 0.844 0.008717 0.828 0.862
## 12.7500 1460 5 0.842 0.008782 0.824 0.859
## 12.8333 1455 2 0.840 0.008808 0.823 0.858
## 12.9167 1425 3 0.839 0.008849 0.821 0.856
## 13.0000 1403 1 0.838 0.008863 0.821 0.856
## 13.0833 1393 1 0.837 0.008877 0.820 0.855
## 13.1667 1364 4 0.835 0.008935 0.818 0.853
## 13.2500 1330 4 0.832 0.008996 0.815 0.850
## 13.3333 1287 2 0.831 0.009029 0.814 0.849
## 13.5000 1230 1 0.830 0.009046 0.813 0.848
## 13.5833 1182 1 0.830 0.009066 0.812 0.848
## 13.6667 1156 2 0.828 0.009107 0.811 0.846
## 13.7500 1119 2 0.827 0.009151 0.809 0.845
## 13.8333 1086 1 0.826 0.009174 0.808 0.844
## 13.9167 1071 1 0.825 0.009198 0.807 0.844
## 14.0833 1037 1 0.825 0.009223 0.807 0.843
## 14.1667 999 2 0.823 0.009278 0.805 0.841
## 14.2500 955 1 0.822 0.009308 0.804 0.840
## 14.3333 931 3 0.819 0.009403 0.801 0.838
## 14.4167 879 2 0.817 0.009474 0.799 0.836
## 14.5000 815 1 0.816 0.009515 0.798 0.835
## 14.9167 676 2 0.814 0.009639 0.795 0.833
## 15.0000 660 2 0.812 0.009766 0.793 0.831
## 15.0833 647 2 0.809 0.009896 0.790 0.829
## 15.1667 628 3 0.805 0.010097 0.786 0.825
## 15.5000 498 3 0.800 0.010418 0.780 0.821
## 15.5833 463 3 0.795 0.010772 0.774 0.817
## 15.9167 340 1 0.793 0.010991 0.772 0.815
##
## BOOZE_q=>2/week
## time n.risk n.event survival std.err lower 95% CI upper 95% CI
## 0.167 2527 4 0.998 0.000791 0.997 1.000
## 0.250 2523 1 0.998 0.000884 0.996 1.000
## 0.333 2522 4 0.996 0.001185 0.994 0.999
## 0.417 2518 1 0.996 0.001249 0.994 0.998
## 0.500 2517 4 0.994 0.001477 0.992 0.997
## 0.583 2513 1 0.994 0.001528 0.991 0.997
## 0.750 2512 1 0.994 0.001578 0.991 0.997
## 0.833 2511 3 0.992 0.001718 0.989 0.996
## 0.917 2508 1 0.992 0.001763 0.989 0.996
## 1.000 2507 2 0.991 0.001848 0.988 0.995
## 1.083 2505 4 0.990 0.002007 0.986 0.994
## 1.167 2501 2 0.989 0.002082 0.985 0.993
## 1.250 2499 1 0.989 0.002119 0.984 0.993
## 1.333 2498 3 0.987 0.002224 0.983 0.992
## 1.417 2495 1 0.987 0.002258 0.983 0.991
## 1.500 2494 3 0.986 0.002357 0.981 0.990
## 1.583 2491 1 0.985 0.002389 0.981 0.990
## 1.750 2490 1 0.985 0.002421 0.980 0.990
## 1.833 2489 2 0.984 0.002483 0.979 0.989
## 2.000 2487 1 0.984 0.002513 0.979 0.989
## 2.083 2486 1 0.983 0.002543 0.978 0.988
## 2.167 2485 1 0.983 0.002573 0.978 0.988
## 2.250 2484 1 0.983 0.002602 0.978 0.988
## 2.333 2483 1 0.982 0.002631 0.977 0.987
## 2.417 2482 1 0.982 0.002659 0.977 0.987
## 2.500 2481 4 0.980 0.002770 0.975 0.986
## 2.583 2477 2 0.979 0.002824 0.974 0.985
## 2.667 2475 1 0.979 0.002851 0.973 0.985
## 2.833 2474 3 0.978 0.002928 0.972 0.984
## 2.917 2471 3 0.977 0.003004 0.971 0.983
## 3.000 2468 6 0.974 0.003149 0.968 0.980
## 3.083 2462 3 0.973 0.003219 0.967 0.979
## 3.167 2459 1 0.973 0.003242 0.966 0.979
## 3.250 2458 3 0.972 0.003310 0.965 0.978
## 3.333 2455 2 0.971 0.003354 0.964 0.977
## 3.417 2453 1 0.970 0.003376 0.964 0.977
## 3.500 2452 3 0.969 0.003441 0.962 0.976
## 3.583 2449 3 0.968 0.003504 0.961 0.975
## 3.667 2446 2 0.967 0.003546 0.960 0.974
## 3.750 2444 1 0.967 0.003566 0.960 0.974
## 3.833 2443 3 0.966 0.003627 0.958 0.973
## 3.917 2440 2 0.965 0.003667 0.958 0.972
## 4.000 2438 4 0.963 0.003745 0.956 0.971
## 4.250 2434 1 0.963 0.003765 0.955 0.970
## 4.333 2433 1 0.962 0.003784 0.955 0.970
## 4.417 2432 2 0.962 0.003822 0.954 0.969
## 4.500 2430 3 0.960 0.003878 0.953 0.968
## 4.583 2427 2 0.960 0.003915 0.952 0.967
## 4.667 2425 4 0.958 0.003988 0.950 0.966
## 4.750 2421 4 0.956 0.004059 0.949 0.964
## 4.833 2417 3 0.955 0.004111 0.947 0.963
## 4.917 2414 2 0.954 0.004146 0.946 0.963
## 5.000 2412 4 0.953 0.004214 0.945 0.961
## 5.083 2408 6 0.951 0.004314 0.942 0.959
## 5.167 2402 1 0.950 0.004330 0.942 0.959
## 5.250 2401 4 0.949 0.004394 0.940 0.957
## 5.333 2397 1 0.948 0.004410 0.940 0.957
## 5.417 2396 4 0.947 0.004473 0.938 0.955
## 5.500 2392 2 0.946 0.004505 0.937 0.955
## 5.583 2390 3 0.945 0.004551 0.936 0.954
## 5.667 2387 3 0.943 0.004596 0.934 0.952
## 5.750 2384 7 0.941 0.004701 0.931 0.950
## 5.833 2377 5 0.939 0.004773 0.929 0.948
## 5.917 2372 4 0.937 0.004830 0.928 0.947
## 6.000 2368 1 0.937 0.004845 0.927 0.946
## 6.167 2367 2 0.936 0.004873 0.926 0.945
## 6.250 2365 2 0.935 0.004901 0.926 0.945
## 6.333 2363 5 0.933 0.004969 0.923 0.943
## 6.417 2358 2 0.932 0.004997 0.923 0.942
## 6.583 2356 3 0.931 0.005037 0.921 0.941
## 6.667 2353 8 0.928 0.005143 0.918 0.938
## 6.750 2345 2 0.927 0.005169 0.917 0.937
## 6.833 2343 1 0.927 0.005182 0.917 0.937
## 6.917 2342 1 0.926 0.005195 0.916 0.937
## 7.000 2341 4 0.925 0.005246 0.915 0.935
## 7.083 2337 2 0.924 0.005271 0.914 0.934
## 7.167 2335 5 0.922 0.005333 0.912 0.933
## 7.250 2330 4 0.920 0.005383 0.910 0.931
## 7.333 2326 4 0.919 0.005431 0.908 0.930
## 7.417 2322 3 0.918 0.005467 0.907 0.928
## 7.500 2319 3 0.917 0.005503 0.906 0.927
## 7.583 2316 7 0.914 0.005585 0.903 0.925
## 7.667 2309 7 0.911 0.005665 0.900 0.922
## 7.750 2302 2 0.910 0.005688 0.899 0.921
## 7.833 2300 3 0.909 0.005722 0.898 0.920
## 8.000 2297 3 0.908 0.005755 0.897 0.919
## 8.083 2294 3 0.907 0.005788 0.895 0.918
## 8.167 2291 2 0.906 0.005810 0.895 0.917
## 8.250 2289 1 0.905 0.005821 0.894 0.917
## 8.333 2288 4 0.904 0.005865 0.892 0.915
## 8.417 2284 4 0.902 0.005908 0.891 0.914
## 8.500 2280 7 0.899 0.005981 0.888 0.911
## 8.583 2273 2 0.899 0.006002 0.887 0.911
## 8.667 2271 5 0.897 0.006054 0.885 0.909
## 8.750 2266 4 0.895 0.006095 0.883 0.907
## 8.833 2262 6 0.893 0.006155 0.881 0.905
## 8.917 2256 5 0.891 0.006205 0.879 0.903
## 9.000 2251 5 0.889 0.006254 0.877 0.901
## 9.083 2246 4 0.887 0.006293 0.875 0.900
## 9.167 2242 4 0.886 0.006331 0.873 0.898
## 9.250 2238 2 0.885 0.006350 0.872 0.897
## 9.333 2236 2 0.884 0.006369 0.872 0.897
## 9.417 2234 4 0.882 0.006407 0.870 0.895
## 9.500 2230 4 0.881 0.006444 0.868 0.894
## 9.583 2226 6 0.879 0.006499 0.866 0.891
## 9.667 2220 3 0.877 0.006526 0.865 0.890
## 9.750 2217 3 0.876 0.006553 0.863 0.889
## 9.833 2214 3 0.875 0.006580 0.862 0.888
## 9.917 2211 1 0.875 0.006589 0.862 0.888
## 10.000 2210 2 0.874 0.006607 0.861 0.887
## 10.083 2208 5 0.872 0.006651 0.859 0.885
## 10.167 2203 5 0.870 0.006694 0.857 0.883
## 10.250 2198 2 0.869 0.006712 0.856 0.882
## 10.333 2196 3 0.868 0.006737 0.855 0.881
## 10.417 2193 7 0.865 0.006797 0.852 0.878
## 10.500 2186 3 0.864 0.006822 0.851 0.877
## 10.583 2183 1 0.863 0.006830 0.850 0.877
## 10.667 2182 6 0.861 0.006880 0.848 0.875
## 10.750 2176 3 0.860 0.006904 0.846 0.874
## 10.833 2173 2 0.859 0.006921 0.846 0.873
## 10.917 2171 5 0.857 0.006961 0.844 0.871
## 11.000 2166 6 0.855 0.007009 0.841 0.869
## 11.083 2160 4 0.853 0.007040 0.839 0.867
## 11.167 2156 1 0.853 0.007048 0.839 0.867
## 11.250 2155 3 0.852 0.007072 0.838 0.866
## 11.333 2152 2 0.851 0.007087 0.837 0.865
## 11.417 2150 3 0.850 0.007110 0.836 0.864
## 11.500 2147 3 0.848 0.007134 0.835 0.863
## 11.583 2144 3 0.847 0.007156 0.833 0.861
## 11.667 2141 6 0.845 0.007202 0.831 0.859
## 11.750 2135 4 0.843 0.007232 0.829 0.858
## 11.833 2131 2 0.843 0.007246 0.828 0.857
## 11.917 2129 1 0.842 0.007254 0.828 0.856
## 12.000 2128 1 0.842 0.007261 0.828 0.856
## 12.083 2127 2 0.841 0.007276 0.827 0.855
## 12.167 2125 5 0.839 0.007312 0.825 0.853
## 12.250 2120 4 0.837 0.007341 0.823 0.852
## 12.333 2116 3 0.836 0.007363 0.822 0.851
## 12.417 2113 8 0.833 0.007419 0.819 0.848
## 12.500 2105 3 0.832 0.007441 0.817 0.847
## 12.583 2102 2 0.831 0.007454 0.817 0.846
## 12.667 2100 5 0.829 0.007489 0.814 0.844
## 12.750 2095 1 0.829 0.007496 0.814 0.843
## 12.833 2094 4 0.827 0.007523 0.812 0.842
## 12.917 2060 2 0.826 0.007537 0.812 0.841
## 13.000 2045 3 0.825 0.007559 0.810 0.840
## 13.083 2032 4 0.823 0.007587 0.809 0.838
## 13.167 1988 5 0.821 0.007625 0.807 0.836
## 13.250 1948 2 0.821 0.007640 0.806 0.836
## 13.333 1886 6 0.818 0.007690 0.803 0.833
## 13.417 1804 7 0.815 0.007753 0.800 0.830
## 13.500 1794 3 0.813 0.007780 0.798 0.829
## 13.583 1720 2 0.812 0.007799 0.797 0.828
## 13.667 1681 5 0.810 0.007851 0.795 0.826
## 13.750 1646 4 0.808 0.007893 0.793 0.824
## 13.833 1612 4 0.806 0.007937 0.791 0.822
## 13.917 1589 3 0.805 0.007970 0.789 0.820
## 14.000 1565 1 0.804 0.007982 0.789 0.820
## 14.083 1538 1 0.803 0.007994 0.788 0.819
## 14.167 1464 2 0.802 0.008020 0.787 0.818
## 14.250 1414 3 0.801 0.008063 0.785 0.817
## 14.333 1387 1 0.800 0.008078 0.784 0.816
## 14.417 1328 2 0.799 0.008111 0.783 0.815
## 14.500 1260 5 0.796 0.008202 0.780 0.812
## 14.583 1220 2 0.794 0.008240 0.778 0.811
## 14.667 1188 1 0.794 0.008260 0.778 0.810
## 14.750 1115 4 0.791 0.008352 0.775 0.807
## 14.833 1041 1 0.790 0.008379 0.774 0.807
## 14.917 1001 1 0.789 0.008407 0.773 0.806
## 15.000 963 2 0.788 0.008469 0.771 0.804
## 15.333 808 2 0.786 0.008560 0.769 0.803
## 15.417 755 3 0.783 0.008714 0.766 0.800
## 15.583 614 3 0.779 0.008946 0.761 0.797
## 15.667 589 1 0.777 0.009028 0.760 0.795
## 15.750 548 1 0.776 0.009123 0.758 0.794
## 15.833 530 2 0.773 0.009320 0.755 0.792
## 15.917 492 1 0.772 0.009433 0.753 0.790
## 16.000 460 1 0.770 0.009560 0.751 0.789
## 16.083 441 1 0.768 0.009697 0.749 0.787
## 16.167 422 1 0.766 0.009843 0.747 0.786
## 16.250 362 3 0.760 0.010422 0.740 0.781
## 16.417 225 1 0.757 0.010910 0.736 0.778
## 16.500 187 2 0.749 0.012201 0.725 0.773
## 16.583 169 1 0.744 0.012908 0.719 0.770
## 16.750 82 1 0.735 0.015618 0.705 0.766
summary(fit)$table
## records n.max n.start events rmean se(rmean) median
## BOOZE_q=0/week 4053 4053 4053 1070 14.42166 0.07071389 NA
## BOOZE_q=0–0.5/week 941 941 941 213 14.83118 0.13643836 NA
## BOOZE_q=0.5–2/week 1729 1729 1729 325 15.15602 0.09331554 NA
## BOOZE_q=>2/week 2527 2527 2527 537 15.03836 0.07729027 NA
## 0.95LCL 0.95UCL
## BOOZE_q=0/week NA NA
## BOOZE_q=0–0.5/week NA NA
## BOOZE_q=0.5–2/week NA NA
## BOOZE_q=>2/week NA NA
#Log-rank test
survdiff(Surv(FU, DEATH)~BOOZE_q, data=d)
## Call:
## survdiff(formula = Surv(FU, DEATH) ~ BOOZE_q, data = d)
##
## N Observed Expected (O-E)^2/E (O-E)^2/V
## BOOZE_q=0/week 4053 1070 916 25.873 45.243
## BOOZE_q=0–0.5/week 941 213 219 0.139 0.155
## BOOZE_q=0.5–2/week 1729 325 411 18.013 22.319
## BOOZE_q=>2/week 2527 537 599 6.493 9.027
##
## Chisq= 50.6 on 3 degrees of freedom, p= 6e-11